The present invention relates to a digital image signal processing apparatus and, more particularly, to apparatus and method for interpolating a digital video signal to produce interpolated video data.
Various techniques for compressing a digital video signal to be recorded or transmitted are known. One such technique is to perform multiplexing sub-Nyquist sampling encoding which is used in the so-called MUSE system, and which consists of "thinning" out (i.e., removing) selected pixels from the digital video signal prior to its transmission and interpolating (i.e., generating) the "thinned" out pixels from the transmitted pixels in a receiving system which receives the compressed digital video signal.
It has been proposed to "up-convert" a standard definition digital video signal to a high definition digital video signal (HDTV) by utilizing pixels in the standard definition signal to produce high definition pixels. Such interpolation may be accomplished by "predicting" the interpolated pixel value using values of known adjacent pixels in the standard definition digital video signal. One technique, known as class categorization, produces an "address" or "class code" from values of pixels which are adjacent to a pixel to be interpolated, and a predicted pixel value of the interpolated data, or coefficient data used to generate the interpolated pixel, is stored in a memory at a location identified by the class code. For example, a class code may be generated from four 8-bit pixel values of pixels in a "block" of data which are adjacent to a pixel to be interpolated and which produce a 32-bit class code. However, since there are 2.sup.32 possible class codes, which require an inordinate amount of memory, the value of each pixel is compressed (e.g., to 3-bits) before the class code is generated.
One method, known as adaptive dynamic range coding (ADRC), compresses pixel values from, for example, 8-bits to 3-bits. In ADRC processing of pixels, the maximum and minimum values of pixels that are each adjacent to a pixel to be interpolated are obtained, and the difference between the minimum and maximum pixel values constitutes the dynamic range of the block. The pixels are normalized by reducing their values by the minimum pixel value of the block, and the normalized pixel values are quantized by the dynamic range of the block thereby producing 3-bit values. The four 3-bit pixel values are utilized to form a 12-bit class code having 4096 possible values.
When the class code of a block of pixels is obtained, four coefficients w.sub.1 to w.sub.4 that correspond to this class code are used to generate a value "x" of the interpolated pixel using the following equation (1), where a, b, c and d are the respective values of the four known pixels. EQU x=aw.sub.1 +bw.sub.2 +cw.sub.3 +dw.sub.4 ( 1)
One disadvantage with the above-described method of classifying a block of pixels is the non-utilization of an important class code. Specifically, when a block is "flat", that is, when the values of all of the pixels in the block are the same, the dynamic range (DR) of the block is zero, thereby resulting in the compressed pixel value of either (000) or (111) for each pixel in the block. In this instance, the class code of the block is either (000000000000) or (111111111111), and thus, these two class codes are not utilized effectively since they both may represent the same "flat" block.
Another disadvantage with the above-described method of classifying a block of pixels is the general inability to distinguish "flat" blocks that have different pixel values. Namely, pixels in a first block whose values are equal to a first value are normalized and quantized to a minimum value and pixels in a second block whose values are equal to a second value are normalized and quantized also to the same minimum value.